Abstract
Demand response (DR) refers to the consumers' activities for changing the load profile with the purpose of lowering cost, improving power quality or reliability of power system. Enhancement in participation of the DR is widely recognized as a profit-making pattern in distribution systems for both residential units (to increase their benefits) and distribution companies (DISCO) (to reduce their peak demand and costs). The target of this research is concentrated on proposing a new strategy for optimal scheduling of flexible loads for the next day. Then, the day ahead pricing (DAP) is modeled using the inclining block rates (IBR), assumed for retail electricity markets, to investigate the efficiency of the proposed strategy. At the same time, the appliances stochastic time of use (ASTOU) are taken into account in residential units for non-controllable part of the load during a day stochastically. Among five various copulas, the Gaussian copula (GC) function shows the best performance in modeling and estimation of non-controllable load consumption. Finally, simulations, performed with the GAMS, illustrate the effectiveness of the suggested approach which is formulated as a stochastic nonlinear programming (NLP) modeled by the GC. Notice that copulas use samples of real data gathered from residential units.
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